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All Journal JOURNAL OF EARTH ENERGY ENGINEERING Jurnal Offshore: Oil, Production Facilities, and Renewable Energy Journal of Earth Energy Science, Engineering, and Technology
Sutiadi, Andrian
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Earth & Planetary Sciences Energy Engineering Materials Science & Nanotechnology Mechanical Engineering

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Journal : Journal of Earth Energy Science, Engineering, and Technology

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Modeling of Shrimp Chitosan Polymer Adsorption Using Artificial Neural Network Fathaddin, Muhammad Taufiq; Mardiana, Dwi Atty; Sutiadi, Andrian; Maulida, Fajri; Ulfah, Baiq Maulinda
Journal of Earth Energy Science, Engineering, and Technology Vol. 7 No. 2 (2024): JEESET VOL. 7 NO. 2 2024
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/jeeset.v7i2.21134

Abstract

One phenomenon that can occur when a polymer solution is injected into an oil reservoir is adsorption. Adsorption occurs due to interactions between polymer molecules and the reservoir pore surface. Adsorption causes some polymer molecules to be removed from solution. So, this process results in a reduction in the polymer concentration in the solution. In this study, an artificial neural network (ANN) model is used to estimate the adsorption of shrimp chitosan polymer on the surface of 40 mesh and 60 mesh sand grains. The ANN model can estimate adsorption more accurately than previous models. This is because previous models only predicted certain adsorption patterns, while the ANN model is able to predict adsorption with complex relationships. The comparison of the mean absolute relative errors (MAREs) of the ANN, Langmuir, Freundlich, Henry, and Harkins-Jura models is 5.7%, 15.9%, 14.6%, 15.2%, and 14.5%, respectively.
Adsorption Modeling of Amorphophallus oncophyllus Prain Using Artificial Neural Network Sutiadi, Andrian; Mardiana, Dwi Atty; Fathaddin, Muhammad Taufiq
Journal of Earth Energy Science, Engineering, and Technology Vol. 7 No. 3 (2024): JEESET VOL. 7 NO. 3 2024
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/qagty424

Abstract

Adsorption is the process of interaction between a liquid and a solid surface. It happens because of physical forces or chemical bonds, which moves substance molecules dissolved in a liquid to the solid surface. As a result, the concentration of the substance in the solution drops. In this study, an artificial neural network (ANN) was applied to model the adsorption of Amorphophallus oncophyllus Prain and xanthan gum on sand grains with sizes of 40 mesh and 60 mesh. Two ANN models were developed. The first ANN model was used to predict the final concentration of the polymer solution after the adsorption process. This model had a correlation coefficient for the training, validation, and testing phases of 0.9968, 0.9982, and 0.9990, respectively. Meanwhile the second ANN model was used to predict the adsorbed polymer. This model had a correlation coefficient for the training, validation, and testing phases of 0.9984, 0.9996, and 0.9985, respectively. These models were capable of accurately predicting the final concentration and adsorbed polymer when compared to laboratory data.
Co-Authors Arkaan, Muhammad Dzaki Dardjat, Izumi Wicaksono Havidh Pramadika Mardiana, Dwi Atty Maulida, Fajri Muhammad Taufiq Fathaddin, Muhammad Taufiq Rakhmanto, Pri Agung Rini Setiati Ristawati, Arinda Siahaya, Jacob Sonny Irawan Ulfah, Baiq Maulinda